The contamination of farmlands with hazardous metals from mining puts the safety of agricultural commodities at risk. For remediation, it is crucial to map the spatial distribution of contaminated soil. Typical sampling-based procedures are time-consuming and labor-intensive. The use of visible, near-infrared, and short-wave infrared reflectance (VNIR-SWIR) spectroscopy to detect soil heavy metal pollution is an alternative. With the aim of investigating a methodology of detecting the most sensitive bands using VNIR-SWIR spectra to find lead (Pb) anomalies in agriculture soil near mining activities, the area in Xiaoqinling Mountain, downstream from a series of active gold mines, was selected to test the feasibility of utilizing VNIR-SWIR spectroscopy to map soil Pb. A total of 115 soil samples were collected for laboratory Pb analysis and spectral measurement. Partial least squares regression (PLSR) was adopted to estimate the soil Pb content by building the prediction model, and the model was optimized by finding the optimal number of bands involved. The spatial distribution of Pb concentration was mapped using the ordinary kriging (OK) interpolation method. This study found that five spectral bands (522 nm, 1668 nm, 2207 nm, 2296 nm, and 2345 nm) were sensitive to soil Pb content. The optimized prediction model’s coefficient of determination (R²), residual prediction deviation (RPD), and root mean square error (RMSE) were 0.711, 1.860, and 0.711 ln(mg/kg), respectively. Additionally, the result of OK interpolation was convincing and accurate (R² = 0.775, RMSE = 0.328 ln(mg/kg)), comparing maps from estimated and ground truth data. This study proves that it is feasible to use VNIR-SWIR spectral data for in situ estimation of the soil Pb content.

Based on the maximum entropy modeling (Maxent) and ArcGIS tool, this study assessed the potential of marginal land and analyzed the impact of environmental variables for Jerusalem artichoke (Helianthus tuberosus L.) in Shaanxi Province, China. The results showed that the dominant land type used for the growth of Jerusalem artichoke was moderately dense grassland. Additionally, significant environmental variables of Jerusalem artichoke and their suitable range in Shaanxi Province were average slope (SLP, 0–5°C), average soil depth (DPT, 1.50–1.60 m), max temperature of the warmest month (Bio5, 30–31°C), annual mean temperature (Bio1, 16.5–18.0°C), precipitation of the wettest quarter (Bio16, 0.01–0.02 m), July solar radiation (SR7, 1.66–1.67 × 10⁷ W/m²), precipitation seasonality (Bio15, 50–60%), precipitation of the driest quarter (Bio17, 0–0.005 m), and isothermality (Bio3, 265–275). Furthermore, the suitable area was mainly distributed in southern (mainly Hanzhong, Ankang, and Shangluo) and northern (mainly Yan’an and Yulin) parts of Shaanxi Province, covering around 8.81 × 10¹⁰ m² and accounting for 42.8% of the total area of the Shaanxi Province. This study can provide a reference for the rational planting of Jerusalem artichoke in Shaanxi Province.

As a foodstuff crop, Jerusalem artichoke has a promising prospect for providing sustainable feed-stock sources for bioenergy development. Due to relatively limited cultivated land resources in China, it is crucial to evaluate Jerusalem artichoke’s potential production capacity in marginal land. Based on Jerusalem artichoke’s growth and photosynthetic characteristics, the agricultural production systems simulator model (APSIM) and multi-factor integrated assessment method were integrated to provide an operational method for comprehensively evaluating the marginal land resources suitable for developing the plantation of Jerusalem artichoke in the Shaanxi province, China. The results showed that 0.73 million ha of marginal land was suitable for Jerusalem artichoke cultivation in the Shaanxi province, and 5.4 million ha of marginal land was fairly suitable for Jerusalem artichoke cultivation, with the yield reaching 44,289 kg/ha and 38,861 kg/ha, respectively. The suitable land resources are mainly located in Yan’an (0.18 million ha), Hanzhong (0.13 million ha), and Baoji (0.08 million ha), most of which are moderate dense grassland (accounting for 50.6% of suitable land), dense grassland (accounting for 16.2% of suitable land), shrubland (accounting for 14.7% of suitable land), and sparse forest land (accounting for 9.18% of suitable land). The findings of this study can be used to establish targeted policies for Jerusalem artichoke development in China and other countries, particularly those along the Silk Road.